Senior/Staff Machine Learning Research Engineer, General Agents, Enterprise GenAI
$265k - $331k • San Francisco, CA; New York, NY
Posted 1mo ago
Job Location
San Francisco, CA; New York, NY
Tech Stack
Remote Work Policy
On-site
Categories
Machine Learning Engineer
About the job
Scale AI is seeking a Senior/Staff Machine Learning Engineer for its General Agents team. This role is crucial in designing, building, and deploying production-ready AI agents to address high-impact enterprise challenges. You will be involved in the entire agent lifecycle, from conceptualization and system design to evaluation, deployment, and ongoing iteration. The position requires bridging cutting-edge agentic techniques with the practical demands of real-world customer environments, focusing on creating scalable, reliable, and generalizable agent systems.
Responsibilities
- Design and implement end-to-end agent systems integrating LLM reasoning, tool use, memory, and control logic.
- Build scalable and reliable agent architectures deployable across diverse customer environments.
- Develop evaluation frameworks, datasets, and metrics to assess agent performance and reliability in production.
- Collaborate with product managers, customers, and engineering teams to translate requirements into agent designs.
- Productionize advanced agent techniques into maintainable and observable systems.
- Own the deployment, monitoring, and iteration of agent systems, including failure analysis.
- Contribute to technical direction and architectural decisions for general agent development.
Requirements
- 5+ years of experience building and deploying production ML or AI systems.
- Bachelor's or Master's degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
- Deep understanding of modern LLMs, prompt/context/system optimization, and agentic system design.
- Proficiency in Python, writing production-quality, testable, and maintainable code.
- Experience building systems that integrate models with external tools, APIs, databases, and services.
- Ability to navigate ambiguous problem spaces, balancing research with product constraints.
- Strong communication skills and experience in cross-functional or customer-facing environments.
Benefits
- Base salary
- Equity
- Comprehensive health, dental, and vision coverage
- Retirement benefits
- Learning and development stipend
- Generous PTO
- Commuter stipend (potential)